CTH-Net: A CNN and Transformer hybrid network for skin lesion segmentation.

Automatically and accurately segmenting skin lesions can be challenging, due to factors such as low contrast and fuzzy boundaries. This paper proposes a hybrid encoder-decoder model (CTH-Net) based on convolutional neural network (CNN) and Transformer, capitalizing on the advantages of these approaches. We propose three modules for skin lesion segmentation and seamlessly connect them with carefully designed model architecture. Better segmentation performance is achieved by introducing SoftPool in the CNN branch and sandglass block in the bottleneck layer. Extensive experiments were conducted on four publicly accessible skin lesion datasets, ISIC 2016, ISIC 2017, ISIC 2018, and PH2 to confirm the efficacy and benefits of the proposed strategy. Experimental results show that the proposed CTH-Net provides better skin lesion segmentation performance in both quantitative and qualitative testing when compared with state-of-the-art approaches. We believe the CTH-Net design is inspiring and can be extended to other applications/frameworks.

Indirect co-culture of osteoblasts and endothelial cells in vitro based on a biomimetic 3D composite hydrogel scaffold to promote the proliferation and differentiation of osteoblasts.

The field of orthopedics has long struggled with the challenge of repairing and regenerating bone defects, which involves a complex process of osteogenesis requiring coordinated interactions among different types of cells. The crucial role of endothelial cells and osteoblasts in bone vascularization and osteogenesis underscores the importance of their intimate interaction. However, efforts to bioengineer bone tissue have been impeded by the difficulty in establishing proper angiogenesis and osteogenesis in tissue structures. This study presents a novel approach to bone tissue engineering, involving a three-dimensional composite hydrogel scaffold composed of sodium alginate microspheres encapsulated in type I collagen. Using this scaffold, a three-dimensional indirect co-culture system was established for osteoblasts and endothelial cells to evaluate the osteogenic differentiation potential of osteoblasts. Results demonstrate that the non-contact co-culture system of endothelial cells and osteoblasts constructed by the composite hydrogel scaffold loaded with microspheres holds promise for bone tissue engineering. The innovative concept of an indirect co-culture system presents exciting prospects for conducting intercellular communication studies and offers a valuable in vitro tissue platform to investigate tissue regeneration.

Transformation of Diffusion and Local Structure of CH4 , CO2 , SO2 and H2 O Mixtures in Graphene Under Wide Temperature and Pressure Range: A Molecular Dynamics Simulation Study.

As a material with high specific surface area and excellent chemical stability, graphene exhibited remarkable adsorption and separation performance as well as a wide range of potential applications. The graphene layer played a significant role in influencing gas transmission. In this study, we employed molecular dynamics simulation to investigate the diffusion characteristics and local structures of a mixed system consisting of CH4 , CO2 , SO2 and H2 O. Additionally, we further examined the transformation of the behavior of these mixtures within graphene layers. The order of diffusion coefficients of the four molecules without graphene was H2 O>SO2 >CO2 ≫CH4 . However, in the double-layer graphene, the order changed to CH4 >CO2 ≫H2 O>SO2 . Higher temperatures and lower pressures were found to facilitate gas diffusion. Temperature and pressure had great effects on the local structures of CH4 , CO2 and SO2 , while their impact on H2 O was limited due to the extensive network of hydrogen bonds formed by H2 O molecules. The statistical results of average coordination number revealed that CH4 tended to aggregate with itself, whereas CO2 and SO2 exhibited a tendency to aggregate with H2 O. The graphene structure enhanced the separation and transportation of CH4 from mixed systems.

Extraordinary-log Universality of Critical Phenomena in Plane Defects.

The recent discovery of the extraordinary-log (E-Log) criticality is a celebrated achievement in modern critical theory and calls for generalization. Using large-scale Monte Carlo simulations, we study the critical phenomena of plane defects in three- and four-dimensional O(n) critical systems. In three dimensions, we provide the first numerical proof for the E-Log criticality of plane defects. In particular, for n=2, the critical exponent q[over ^] of two-point correlation and the renormalization-group parameter α of helicity modulus conform to the scaling relation q[over ^]=(n-1)/(2πα), whereas the results for n≥3 violate this scaling relation. In four dimensions, it is strikingly found that the E-Log criticality also emerges in the plane defect. These findings have numerous potential realizations and would boost the ongoing advancement of conformal field theory.

Self-Distillation for Randomized Neural Networks.

Knowledge distillation (KD) is a conventional method in the field of deep learning that enables the transfer of dark knowledge from a teacher model to a student model, consequently improving the performance of the student model. In randomized neural networks, due to the simple topology of network architecture and the insignificant relationship between model performance and model size, KD is not able to improve model performance. In this work, we propose a self-distillation pipeline for randomized neural networks: the predictions of the network itself are regarded as the additional target, which are mixed with the weighted original target as a distillation target containing dark knowledge to supervise the training of the model. All the predictions during multi-generation self-distillation process can be integrated by a multi-teacher method. By induction, we have additionally arrived at the methods for infinite self-distillation (ISD) of randomized neural networks. We then provide relevant theoretical analysis about the self-distillation method for randomized neural networks. Furthermore, we demonstrated the effectiveness of the proposed method in practical applications on several benchmark datasets.

The dosage of curcumin to alleviate movement symptoms in a 6-hydroxydopamine-induced Parkinson's disease rat model.

Background: Curcumin is a natural compound with extensive pharmacological effects. This research is to verify the optimal dose and administration duration efficacy of curcumin in alleviating the movement symptoms of Parkinson's disease (PD). Methods: Wistar rats were divided into six groups including control, model, levodopa treatment and low/middle/high (40/80/160 mg/kg/d) curcumin treatment groups. After stereotactic brain injection of 6-hydroxydopamine (6-OHDA), curcumin was given by intragastric administration for 2 weeks. To evaluate the drug effect, the rats received behavioral tests including apomorphine (APO)-induced rotation test, rotarod test and open field test. Then the rats were sacrificed and the brain slices including substantia nigra pars compacta (SNc) were used for immunofluorescence staining. Results: After 6-OHDA injection, the model group showed typical movement symptoms including the severe APO-induced rotation to the healthy side, decreased latency in the rotarod with constant or accelerative mode, and decreased total distance and average speed in the open field test. In the results of immunofluorescence staining, the 6-OHDA induced a severe damage of dopaminergic neurons in SNc. The 160 mg/kg/d treatment of curcumin to intervene for 2 weeks alleviated most of the behavioral disorders but the 40/80 mg/kg/d treatment showed limitations. Then, we compared the effect of 1 week intervention to the 2 weeks with 160 mg/kg/d treatment of curcumin to intervene and results indicated that the treatment of 2 weeks could better alleviate the symptoms. Conclusions: Curcumin alleviated 6-OHDA-induced movement symptoms in a PD rat model. Additionally, the effect of curcumin against PD indicated dose and duration dependent and the intervention of 160 mg/kg/d for 2 weeks showed optimally therapeutic effect.

Online dynamic ensemble deep random vector functional link neural network for forecasting.

This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's representation ability. Each hidden layer's representation is utilized for training an output layer, and the ensemble of all output layers forms the edRVFL's output. However, the original edRVFL is not designed for online learning, and the randomized nature of the features is harmful to extracting meaningful temporal features. In order to address the limitations and extend the edRVFL to an online learning mode, this paper proposes a dynamic edRVFL consisting of three online components, the online decomposition, the online training, and the online dynamic ensemble. First, an online decomposition is utilized as a feature engineering block for the edRVFL. Then, an online learning algorithm is designed to learn the edRVFL. Finally, an online dynamic ensemble method, which can measure the change in the distribution, is proposed for aggregating all layers' outputs. This paper evaluates and compares the proposed model with state-of-the-art methods on sixteen time series.

Enhancer RNAs in transcriptional regulation: recent insights.

Enhancers are a class of cis-regulatory elements in the genome that instruct the spatiotemporal transcriptional program. Last decade has witnessed an exploration of non-coding transcripts pervasively transcribed from active enhancers in diverse contexts, referred to as enhancer RNAs (eRNAs). Emerging evidence unequivocally suggests eRNAs are an important layer in transcriptional regulation. In this mini-review, we summarize the well-established regulatory models for eRNA actions and highlight the recent insights into the structure and chemical modifications of eRNAs underlying their functions. We also explore the potential roles of eRNAs in transcriptional condensates.

Curcumin (CUMINUP60®) mitigates exercise fatigue through regulating PI3K/Akt/AMPK/mTOR pathway in mice.

Curcumin is a chemical constituent extracted from Curcuma longa L. Several clinical and preclinical studies have demonstrated that it can mitigate exercise fatigue, but the exact mechanism is still unknown. Therefore, we applied a mouse model of exercise fatigue to investigate the possible molecular mechanisms of curcumin's anti-fatigue effect. Depending on body mass, Kunming mice were randomly divided into control, caffeine (positive drug), and curcumin groups, and were given 28 days intragastric administration. Both the caffeine group and curcumin group showed significant improvement in exercise fatigue compared to the control group, as evidenced by the increase in time to exhaustion, as well as the higher quadriceps coefficient, muscle glycogen (MG) content, and increase in the expression of Akt, AMPK, PI3K, and mTOR proteins. While the curcumin group also significantly improved the exercise fatigue of the mice, demonstrating a lower AMP/ATP ratio and lactic acid (LA) content, and increased glycogen synthase (GS), and myonectin content compared to the caffeine group. Therefore, in the present study, we found that curcumin can exert a similar anti-fatigue effect to caffeine and may act by regulating energy metabolism through modulating the expression of the proteins in the PI3K/Akt/AMPK/mTOR pathway.

Effect of the uronic acid composition of alginate in alginate/collagen hybrid hydrogel on chondrocyte behavior.

Introduction: Developing a culture system that can effectively maintain chondrocyte phenotype and functionalization is a promising strategy for cartilage repair. Methods: An alginate/collagen (ALG/COL) hybrid hydrogel using different guluronate/mannuronate acid ratio (G/M ratio) of alginates (a G/M ratio of 64/36 and a G/M ratio of 34/66) with collagen was developed. The effects of G/M ratios on the properties of hydrogels and their effects on the chondrocytes behaviors were evaluated. Results: The results showed that the mechanical stiffness of the hydrogel was significantly affected by the G/M ratios of alginate. Chondrocytes cultured on Mid-G/M hydrogels exhibited better viability and phenotype preservation. Moreover, RT-qPCR analysis showed that the expression of cartilage-specific genes, including SOX9, COL2, and aggrecan was increased while the expression of RAC and ROCK1 was decreased in chondrocytes cultured on Mid-G/M hydrogels. Conclusion: These findings demonstrated that Mid-G/M hydrogels provided suitable matrix conditions for cultivating chondrocytes and may be useful in cartilage tissue engineering. More importantly, the results indicated the importance of taking alginate G/M ratios into account when designing alginate-based composite materials for cartilage tissue engineering.

Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma.

High-grade neuroblastoma (HG-NB) exhibits a significantly diminished survival rate in comparison to low-grade neuroblastoma (LG-NB), primarily attributed to the mechanism of HG-NB is unclear and the lacking effective therapeutic targets and diagnostic model. Therefore, the current investigation aims to study the dysregulated network between HG-NB and LG-NB based on transcriptomics and metabolomics joint analysis. Meanwhile, a risk diagnostic model to distinguish HG-NB and LG-NB was also developed. Metabolomics analysis was conducted using plasma samples obtained from 48 HG-NB patients and 36 LG-NB patients. A total of 39 metabolites exhibited alterations, with 20 showing an increase and 19 displaying a decrease in HG-NB. Additionally, transcriptomics analysis was performed on NB tissue samples collected from 31 HG-NB patients and 20 LG-NB patients. Results showed that a significant alteration was observed in a total of 1,199 mRNAs in HG-NB, among which 893 were upregulated while the remaining 306 were downregulated. In particular, the joint analysis of both omics data revealed three aberrant pathways, namely the cAMP signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway, which were found to be associated with cell death. Notably, a diagnostic model for HG-NB risk classification was developed based on the genes MGST1, SERPINE1, and ERBB3 with an area under the receiver operating characteristic curve of 0.915. In the validation set, the sensitivity and specificity were determined to be 75.0% and 80.0%, respectively.

Dynamics of soil microbial communities involved in carbon cycling along three successional forests in southern China.

Dynamics of plant communities during forest succession have been received great attention in the past decades, yet information about soil microbial communities that are involved in carbon cycling remains limited. Here we investigated soil microbial community composition and carbohydrate degradation potential using metagenomic analysis and examined their influencing factors in three successional subtropical forests in southern China. Results showed that the abundances of soil bacteria and fungi increased (p ≤ 0.05 for both) with forest succession in relation to both soil and litter characteristics, whereas the bacterial diversity did not change (p > 0.05) and the fungal diversity of Shannon-Wiener index even decreased (p ≤ 0.05). The abundances of microbial carbohydrate degradation functional genes of cellulase, hemicellulase, and pectinase also increased with forest succession (p ≤ 0.05 for all). However, the chitinase gene abundance did not change with forest succession (p > 0.05) and the amylase gene abundance decreased firstly in middle-succession forest and then increased in late-succession forest. Further analysis indicated that changes of functional gene abundance in cellulase, hemicellulase, and pectinase were primarily affected by soil organic carbon, soil total nitrogen, and soil moisture, whereas the variation of amylase gene abundance was well explained by soil phosphorus and litterfall. Overall, we created a metagenome profile of soil microbes in subtropical forest succession and fostered our understanding of microbially-mediated soil carbon cycling.

A novel curcumin oil solution can better alleviate the motor activity defects and neuropathological damage of a Parkinson's disease mouse model.

Curcumin has been reported to improve or prevent movement disorders in Parkinson's disease (PD); however, its low bioavailability is the biggest obstacle to its application. To optimize the limited efficacy of curcumin and to improve its protective effects against PD, we prepared and tested a novel curcumin oil solution. In vivo imaging was used to confirm that the curcumin oil solution has higher bioavailability than curcumin alone. To test its motor effects on 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced movement disorders, behavioral tests, including the open-field test, pole test, rotarod test, and automated gait analysis were used. Finally, pathological evaluation using immunohistochemistry and western blotting analysis was done. Encouragingly, the behavioral test findings exhibited a better protective effect against MPTP-induced movement disorders. In addition, it had a greater protective effect on dopaminergic neurons in the compact part of the substantia nigra along with the PD process according to pathological evaluation. This novel curcumin oil solution may provide a new choice for PD prevention as a dietary supplement or clinically assisted treatment based on its better bioavailability and efficiency.

Oxytocin and serotonin in the modulation of neural function: Neurobiological underpinnings of autism-related behavior.

Autism spectrum disorders (ASD) is a group of generalized neurodevelopmental disorders. Its main clinical features are social communication disorder and repetitive stereotyped behavioral interest. The abnormal structure and function of brain network is the basis of social dysfunction and stereotyped performance in patients with autism spectrum disorder. The number of patients diagnosed with ASD has increased year by year, but there is a lack of effective intervention and treatment. Oxytocin has been revealed to effectively improve social cognitive function and significantly improve the social information processing ability, empathy ability and social communication ability of ASD patients. The change of serotonin level also been reported affecting the development of brain and causes ASD-like behavioral abnormalities, such as anxiety, depression like behavior, stereotyped behavior. Present review will focus on the research progress of serotonin and oxytocin in the pathogenesis, brain circuit changes and treatment of autism. Revealing the regulatory effect and neural mechanism of serotonin and oxytocin on patients with ASD is not only conducive to a deeper comprehension of the pathogenesis of ASD, but also has vital clinical significance.

Expression and Clinical Significance of Th1/Th2/Th17 Cytokines and Lymphocyte Subsets in PCNSL.

Purpose: Primary central nervous system lymphoma (PCNSL) responds favorably to radiation, chemotherapy and targeted drug therapy. However survival is usually worse, the treatment-related drug resistance and recurrence are still clinical problems to be solved urgently. Studies have shown that cytokines are expressed in varying degrees in patients with lymphoma, which is significantly related to the progression, poor prognosis and drug resistance of lymphoma. We explore the expression and clinical significance of Th1/Th2/Th17 cytokines and lymphocyte subsets in patients with PCNSL to provide a more sufficient theoretical basis for its diagnosis and treatment. Patients and Methods: We measured and analysed the levels of Th1/Th2/Th17 cytokines and the distribution of lymphocyte subsets (including Treg cells, CD3+, CD4+, CD8+, CD19+, and CD4+/CD8+) in 39 patients with PCNSL and 96 patients with diffuse large B-cell lymphoma (DLBCL) without central nervous system involvement. The cytokines of 13 healthy people and the lymphocyte subsets of 27 healthy people were measured as the control group. Results: We found a significant difference in the level of Th1/Th2/Th17 cytokines and lymphocyte subsets between PCNSL and healthy controls, especially IL-2, after treatment, which was significantly higher than before treatment (p<0.01). However, the level of CD19+ and CD4+/CD8+ decreased while CD8+ and CD3+ increased after treatment (regardless of whether the treatment was effective), and the difference was statistically significant. In addition, our analysis of different prognostic factors found that HD-MTX-based chemotherapy appears to have a longer progression-free survival and overall survival than osimertinib-based chemotherapy. Conclusion: There are significant differences in Th1/Th2/Th17 cytokines and lymphocyte subsets among PCNSL, DLBCL, and healthy controls, and their detection is helpful for the diagnosis, treatment, and prognosis of PCNSL. HD-MTX-based chemotherapy may still be the first choice for PCNSL.

DDX5: an expectable treater for viral infection- a literature review.

Background and Objective: DEAD-box protein (DDX)5 plays important roles in multiple aspects of cellular processes that require modulating RNA structure. Alongside the canonical role of DDX5 in RNA metabolism, many reports have shown that DDX5 influences viral infection by directly interacting with viral proteins. However, the functional role of DDX5 in virus-associated cancers, as well as the identity of DDX5 in virus infection-associated signaling pathways, has remained largely unexplained. Here, we further explore the precise functions of DDX5 and its potential targets for antiviral treatment. Methods: We searched the PubMed and PMC databases to identify studies on role of DDXs, especially DDX5, during various viral infection published up to May 2022. Key Content and Findings: DDX5 functions as both a viral infection helper and inhibitor, which depends on virus type. DDXs proteins have been identified to play roles on multiple aspects covering RNA metabolism and function. Conclusions: DDX5 influences viral pathogenesis by participating in viral replication and multiple viral infection-related signaling pathways, it also plays a double-edge sword role under different viral infection conditions. Deep investigation into the mechanism of DDX5 modulating immune response in host cells revealed that it holds highly potential usage for future antiviral therapy. We reviewed current studies to provide a comprehensive update of the role of DDX5 in viral infection.

Evaluation of the Effect of Food on the Pharmacokinetics of SHR6390, An Oral CDK4/6 Inhibitor, in Healthy Volunteers.

BACKGROUND AND INTRODUCTION: SHR6390 is a new developed highly effective and selective small-molecule oral CDK4/6 inhibitor. We aimed to evaluate the effect of food on the pharmacokinetics of SHR6390 tablets. METHODS: In an open-label two-way crossover study, 24 healthy Chinese volunteers were randomly divided into Group A and Group B, and 12 volunteers in each group received a single oral dose of a SHR6390 150-mg tablet under fasting and high-fat conditions. Blood samples were collected and determined for pharmacokinetic analyses. A liquid chromatography-tandem mass spectrometry method was developed and validated for determining the SHR6390 concentration. RESULTS: The time to maximum plasma concentration was not significantly affected by a high-fat diet. Compared with the fasting group, maximum plasma concentration, i.e., the area under the concentration-time curve (AUC0-t and AUC0-∞) was altered significantly, as evidenced by an increase of 56.9%, 38.6%, and 37.5% respectively. We identified seven metabolites of SHR6390 from the plasma samples, and we found no sex differences in metabolic pathways. All treatment-emergent adverse events were Grade 1 or 2. CONCLUSIONS: Food intake increased the maximum plasma concentration, AUC0-t, and AUC0-∞ significantly compared with the fasting condition. Meanwhile, single-dose SHR6390 for two treatment cycles is safe. SHR6390 was administered in a fasting status in the pivotal phase III study (NCT03927456) and chosen for the final drug label.

A polygenic stacking classifier revealed the complicated platelet transcriptomic landscape of adult immune thrombocytopenia.

Immune thrombocytopenia (ITP) is an autoimmune disease with the typical symptom of a low platelet count in blood. ITP demonstrated age and sex biases in both occurrences and prognosis, and adult ITP was mainly induced by the living environments. The current diagnosis guideline lacks the integration of molecular heterogenicity. This study recruited the largest cohort of platelet transcriptome samples. A comprehensive procedure of feature selection, feature engineering, and stacking classification was carried out to detect the ITP biomarkers using RNA sequencing (RNA-seq) transcriptomes. The 40 detected biomarkers were loaded to train the final ITP detection model, with an overall accuracy 0.974. The biomarkers suggested that ITP onset may be associated with various transcribed components, including protein-coding genes, long intergenic non-coding RNA (lincRNA) genes, and pseudogenes with apparent transcriptions. The delivered ITP detection model may also be utilized as a complementary ITP diagnosis tool. The code and the example dataset is freely available on http://www.healthinformaticslab.org/supp/resources.php.

Extraordinary-Log Surface Phase Transition in the Three-Dimensional XY Model.

Universality is a pillar of modern critical phenomena. The standard scenario is that the two-point correlation algebraically decreases with the distance r as g(r)∼r^{2-d-η}, with d the spatial dimension and η the anomalous dimension. Very recently, a logarithmic universality was proposed to describe the extraordinary surface transition of the O(N) system. In this logarithmic universality, g(r) decays in a power of logarithmic distance as g(r)∼(lnr)^{-η[over ^]}, dramatically different from the standard scenario. We explore the three-dimensional XY model by Monte Carlo simulations, and provide strong evidence for the emergence of logarithmic universality. Moreover, we propose that the finite-size scaling of g(r,L) has a two-distance behavior: simultaneously containing a large-distance plateau whose height decays logarithmically with L as g(L)∼(lnL)^{-η[over ^]^{'}} as well as the r-dependent term g(r)∼(lnr)^{-η[over ^]}, with η[over ^]^{'}≈η[over ^]-1. The critical exponent η[over ^]^{'}, characterizing the height of the plateau, obeys the scaling relation η[over ^]^{'}=(N-1)/(2πα) with the RG parameter α of helicity modulus. Our picture can also explain the recent numerical results of a Heisenberg system. The advances on logarithmic universality significantly expand our understanding of critical universality.